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In a previous study, Huang et al. used the Alfvén Wave Solar atmosphere Model, one of the widely used solar wind models in the community, driven by ADAPT-GONG magnetograms to simulate the solar wind in the last solar cycle and found that the optimal Poynting flux parameter can be estimated from either the open field area or the average unsigned radial component of the magnetic field in the open field regions. It was also found that the average energy deposition rate (Poynting flux) in the open field regions is approximately constant. In the current study, we expand the previous work by using GONG magnetograms to simulate the solar wind for the same Carrington rotations and determine if the results are similar to the ones obtained with ADAPT-GONG magnetograms. Our results indicate that similar correlations can be obtained from the GONG maps. Moreover, we report that ADAPT-GONG magnetograms can consistently provide better comparisons with 1 au solar wind observations than GONG magnetograms, based on the best simulations selected by the minimum of the average curve distance for the solar wind speed and density.

Solar wind forecasting plays a crucial role in space weather prediction, yet significant uncertainties persist duet to incomplete magnetic field observations of the Sun. Isolating the solar wind forecasting errors due to these effects is difficult. This study investigates the uncertainties in solar wind models arising from these limitations. We simulate magnetic field maps with known uncertainties, including far-side and polar field variations, as well as resolution and sensitivity limitations. These maps serve as input for three solar wind models: the Wang–Sheeley–Arge, the Heliospheric Upwind eXtrapolation, and the European Heliospheric FORecasting Information Asset. We analyze the discrepancies in solar wind forecasts, particularly the solar wind speed at Earth’s location, by comparing the results of these models to a created ground truth magnetic field map, which is derived from a synthetic solar rotation evolution using the Advective Flux Transport model. The results reveal significant variations within each model with a root mean square error ranging from 59 to 121 km s−1. Further comparison with the thermodynamic Magnetohydrodynamic Algorithm outside a Sphere model indicates that uncertainties in the different models can lead to even larger variations in solar wind forecasts compared to those within a single model. However, predicting a range of solar wind velocities based on a cloud of points around Earth can help mitigate uncertainties by up to 20%–77%.

We explore the capabilities of time-dependent (TD) magnetohydrodynamic (MHD) solar wind simulations with the coupled Wang–Sheeley–Arge (WSA) model of the solar corona and the Grid Agnostic MHD for Extended Research Applications model of the inner heliosphere. We compare TD with steady-state (SS) simulations and in situ observations from multiple spacecraft (Earth, STEREO-A, Parker Solar Probe). We show that TD predictions, although better than SS predictions, substantially mispredict the solar wind at different heliospheric locations. We identified three reasons for that: (1) the uncalibrated WSA velocity formula used to generate solar wind velocities at the inner boundary of a heliospheric domain, (2) the extraction of the WSA boundary conditions for input into MHD models very high in the corona, and (3) the abrupt and partial emergence of active regions from the solar east limb. Evaluation of 1 year of TD predictions at the Earth and STEREO-A locations shows that tuning accordingly the WSA relationship when used with MHD models and extracting the WSA boundary conditions lower in the corona (at 5 Rs instead of 21.5 Rs) can lead to improved predictions. However, the abrupt emergence of active regions from the east limb of the Sun, which can highly disrupt the magnetic field topology in the corona, is a difficult task to deal with since complete knowledge of the conditions on the solar far side is not currently available. Solar Orbiter Polarimetric and Helioseismic Imager data can help mitigate this effect; however, unless we get a 4π view of the Sun, we will be unable to completely address it.

Using Bayesian analyses we study the solar electron density with the NANOGrav 11 yr pulsar timing array (PTA) data set. Our model of the solar wind is incorporated into a global fit starting from pulse times of arrival. We introduce new tools developed for this global fit, including analytic expressions for solar electron column densities and open source models for the solar wind that port into existing PTA software. We perform an ab initio recovery of various solar wind model parameters. We then demonstrate the richness of information about the solar electron density, n E , that can be gleaned from PTA data, including higher order corrections to the simple 1/r 2 model associated with a free-streaming wind (which are informative probes of coronal acceleration physics), quarterly binned measurements of n E and a continuous time-varying model for n E spanning approximately one solar cycle period. Finally, we discuss the importance of our model for chromatic noise mitigation in gravitational-wave analyses of pulsar timing data and the potential of developing synergies between sophisticated PTA solar electron density models and those developed by the solar physics community.

Solar wind streams, acting as a background, govern the propagation of space weather drivers in the heliosphere, which induce geomagnetic storm activities. Therefore, predictions of the solar wind parameters are the core of space weather forecasts. This work presents an indigenous three-dimensional (3D) solar wind model (SWASTi-SW). This numerical framework for forecasting the ambient solar wind is based on a well-established scheme that uses a semiempirical coronal model and a physics-based inner heliospheric model. This study demonstrates a more generalized version of the Wang–Sheeley–Arge relation, which provides a speed profile input to the heliospheric domain. Line-of-sight observations of GONG and Helioseismic and Magnetic Imager magnetograms are used as inputs for the coronal model, which in turn provides the solar wind plasma properties at 0.1 au. These results are then used as an initial boundary condition for the magnetohydrodynamics model of the inner heliosphere to compute the solar wind properties up to 2.1 au. Along with the validation run for multiple Carrington rotations, the effect of variation of specific heat ratio and study of the stream interaction region (SIR) are also presented. This work showcases the multidirectional features of SIRs and provides synthetic measurements for potential observations from the Solar Wind Ion Spectrometer subsystem of the Aditya Solar wind Particle Experiment payload on board ISRO’s upcoming solar mission Aditya-L1.

Whether solar wind electrons expanding into the heliosphere can preserve information about their origin in the solar corona remains an open debate. The suprathermal strahl temperature has often been postulated as an indicator of source coronal electron temperature, while the core electron temperature has also been found to correlate with the solar wind velocity in the inner heliosphere. Here we investigate how well solar wind electron populations retain imprints of coronal electron temperature. Using Solar Orbiter measurements at ∼0.5 au, we fit three components (i.e., the core, halo, and strahl) of the electron velocity distribution function and compare the resulting strahl and core temperatures with heavy-ion charge-state ratios, which serve as proxies for the coronal electron temperature. We present the first clear evidence from inner heliosphere observations that, in several individual streams, a proxy for the strahl parallel temperature, Tstrahl,∥, correlates significantly and positively with the charge-state ratios O7+/O6+ and C6+/C5+. However, this correlation is not universally present, implying that many electron streams are significantly affected by transport processes, such as scattering, that erase the signature. We find that, notably, the core perpendicular temperature ( Tcore,⊥ ) also strongly correlates with the charge-state ratios. We interpret this result within the framework of the exospheric solar wind model. Our results suggest that both thermal and suprathermal electrons can at times retain coronal information, but that aggregating multiple streams can obscure the underlying relationships.

The heating and acceleration of the solar wind remains one of the unsolved fundamental problems in heliophysics. It is usually observed that the proton temperature T i is highly correlated with the solar wind speed V SW, while the electron temperature T e shows anticorrelation or no clear correlation with the solar wind speed. Here, we inspect both Parker Solar Probe (PSP) and WIND data, and compare the observations with simulation results. PSP observations below 30 solar radii clearly show a positive correlation between the proton temperature and the wind speed and a negative correlation between the electron temperature and the wind speed. One year (2019) of WIND data confirm that the proton temperature is positively correlated with the solar wind speed, but the electron temperature increases with the solar wind speed for slow wind, while it decreases with the solar wind speed for fast wind. Using a 1D Alfvén-wave-driven solar wind model with different proton and electron temperatures, we find, for the first time, that if most of the dissipated Alfvén wave energy heats the ions instead of the electrons, a positive T i –V SW correlation and a negative T e –V SW correlation arise naturally. If the electrons gain a small but finite portion of the dissipated wave energy, the T e –V SW correlation evolves with the radial distance to the Sun, such that the negative correlation gradually turns positive. The model results show that Alfvén waves are one of the possible explanations for the observed evolution of the proton and electron temperatures in the solar wind.

The physical processes in the solar corona that shape the solar wind remain an active research topic. Modeling efforts have shown that energy and plasma exchanges near the transition region play a crucial role in modulating solar wind properties. Although these regions cannot be measured in situ, plasma parameters can be inferred from coronal spectroscopy and ionization states of heavy ions, which remain unchanged as they escape the corona. We introduce a new solar wind model extending from the chromosphere to the inner heliosphere, capturing thermodynamic coupling across atmospheric layers. By including neutral and charged particle interactions, we model the transport and ionization processes of the gas through the transition region and corona and into the solar wind. Instead of explicitly modeling coronal heating, we link its spatial distribution to large-scale magnetic field properties. Our results confirm that energy deposition strongly affects wind properties through key mechanisms involving chromospheric evaporation, thermal expansion, and magnetic flux expansion. For sources near active regions, the model predicts significant solar wind acceleration, with plasma outflows comparable to those inferred from coronal spectroscopy. For winds from large coronal holes, the model reproduces the observed anticorrelation between charge state and wind speed. However, the predicted charge state ratios are overall lower than observed. Inclusion of a population of energetic electrons enhances both heavy ion charge states and solar wind acceleration, improving agreement with observations.

We apply nested-sampling Bayesian analysis to a model for the transport of magnetohydrodynamic-scale solar wind fluctuations. The dual objectives are to obtain improved constraints on parameters present in the turbulence transport model (TTM) and to support quantitative comparisons of the quality of distinct versions of the transport model. The TTMs analyzed are essentially the 1D steady-state ones presented in Breech et al. that describe the radial evolution of the energy, correlation length, and normalized cross helicity of the fluctuations, together with the proton temperature, in prescribed background solar wind fields. Modeled effects present in the TTM include nonlinear turbulence interactions, shear driving, and energy injection associated with pickup-ions. Each of these modeled effects involves adjustable parameters that we seek to constrain using Bayesian analysis. We find that, given the TTMs and observational data sets analyzed, the most appropriate TTM to recommend corresponds to 2D fluctuations and has von Kármán–Howarth parameters of α ≈ 0.16 and β ≈ 0.10, along with reasonably standard values for the other adjustable parameters. The analysis also indicates that it is advantageous to include pickup ion effects in the lengthscale evolution equation by assuming Z2β/αλ is locally conserved. Such Bayesian analysis is readily extended to more sophisticated solar wind models, space weather models, and might lead to improved predictions of, for example, solar flare and coronal mass ejection interactions with the Earth.

Solar quiet regions are divided into coronal hole regions (CH) and quiet-Sun regions (QS). The global magnetic field in CH is considered open to interplanetary space, while that in QS is closed. To constrain the solar atmosphere and solar wind model, we statistically compared CH and QS in the chromosphere by quantitatively analyzing all available high-resolution spectral data sets of polar off-limb regions taken from the entire catalog of the Interface Region Imaging Spectrograph (IRIS) satellite. We extracted the characteristic quantities from the Mg ii h and k line profiles and compared the dependence of those quantities on the height from the photospheric limb. The main findings are as follows. First, the integrated intensities in the Mg ii k line show a steeper decrease with height in QS while they remain bright at higher altitudes in CH. Second, the unsigned line-of-sight velocities in the Mg ii k line generally increase with height in both regions, although the unsigned velocities increase with height more strongly in QS than in CH. Third, the Mg ii k line widths increase just above the limb and then decrease with height in both CH and QS, but are overall larger for CH than for QS, especially at the lower altitudes. Finally, we found the ratio of the Mg ii k and h lines to show a two-step increase with height in both regions. The results suggest the spicules are higher in CH, and the CH chromosphere exhibits faster motions than the QS.